Hidden Markov models (HMMs) have proven useful in various aspects of speech technology from automatic speech recognition through speech synthesis, speech segmentation and grapheme...
Udochukwu Kalu Ogbureke, Peter Cahill, Julie Carso...
Abstract-- In the paper, we present a real-time speech recognition chip for monosyllables such as A, B, ..., etc. The chip recognizes up to 64 monosyllables based on the Hidden Mar...
Hidden Markov Models (HMMs) provide a simple and effective framework for modelling time-varying spectral vector sequences. As a consequence, almost all present day large vocabula...
We address the problem in signal classification applications, such as automatic speech recognition (ASR) systems that employ the hidden Markov model (HMM), that it is necessary to...
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...